Literature Review.   The problem of determining whether an admissible model set [1]} can generate a finite sequence of experimental input-output data,  known as model (in)validation, is useful for many control applications, including fault diagnosis and model identification [2]}, [3]}. Several approaches for model invalidation have been recently developed for linear parameter varying systems [4]}, [5]}, nonlinear systems [6]}, switched auto-regressive models [7]}, switched affine systems [2]}, [9]}, etc., when their mathematical models are given.
Similarly, when mathematical models are available, abstraction approaches have been widely studied for linear systems [10]}, nonlinear systems [11]}, [12]}, uncertain affine and nonlinear systems [13]}, [3]}, and discrete-time hybrid systems [15]} in order to find simpler dynamics/systems that share most properties of interest with the original system dynamics for the sake of reducing computational complexity. However, these approaches are not applicable when accurate mathematical models are unavailable.
